Cystic fibrosis (CF) patients are highly susceptible to persistent endobronchial infection by Pseudomonas aeruginosa, a common environmental microbe that readily adapts to the CF-lung. Evolutionary adaptations that lead to chronic infection arise from large-scale changes in genome architecture such as insertion, translocation, duplication and deletion, as well as small-scale changes such as single-base pair substitutions. Among clinical strains, small- and large- scale changes are thought to be more commonly transmitted vertically than horizontally. How then do Pseudomonas populations generate sufficient variation to evolve rapidly under the selective pressures of constant immune system surveillance and intermittent antibiotic treatment? (PARAGRAPH) "Mutators," bacteria that have high background mutation rates, are frequently observed in chronic, but not acute, infections, suggesting that clones defective in DNA repair may play an important role in producing genetic variation. We will address this possibility via a two-pronged approach. We will conduct a longitudinal genomic study of strains isolated from multiple CF patients at the Necker Children's Hospital in Paris, France. We will compare the tempo and mode of genome evolution in "mutator" and "non-mutator" lineages. Concurrently, we will develop and test mathematical models that predict the conditions under which mutators emerge and persist. To date, we have produced genomic fingerprints for each clinical isolate, phenotyped each with respect to antibiotic resistance, mucoid status, and frequency of spontaneous rifampicin-resistant mutants. We define "mutators" as clones that produce RifR mutants at a frequency ten-fold greater than the population median. Our preliminary data have led us to hypothesize that: (1) Pseudomonas in the CF-lung evolves by periodic selection of adaptively favored clones, (2) specific defects in different DNA repair result in different background mutation rates, (3) "mutators" increase genetic variation over what we might expect in non-mutator populations, (4) mutator-containing lineages evolve more rapidly than non-mutator lineages. We will test these hypotheses by: performing microarray-based comparative genomic hybridization (a-CGH) to detect strain-specific deletions and duplications and localize breakpoints to single-gene resolution; using multilocus sequence typing (MLST) to estimate small-scale genomic change and infer clonal phylogeny; screening DNA repair gene sequences to determine the basis for each "mutator;" and developing and testing continuous mathematical models that predict conditions for emergence and persistence of mutators. Specifically, we will extend continuous models we have developed to include competition and asynchronous generations, then estimate mutation and reversion rates under conditions where we can control for generation time, population density, and levels of antibiotic. (PARAGRAPH) We will be assisted in these efforts by undergraduates engaged in mentored research. Undergraduate team members will work through an annual cycle supported by fellowships, receive upper-division credit, give formal presentations at local and national conferences, and help bring key aspects of this project into the classroom. Our Specific Aims advance the overall NIH-AREA mission to support pilot, health-related research projects at predominantly undergraduate institutions, as well as specific National Institute of Allergy and Infectious Diseases objectives to support meritorious research in the areas of pathogen genomics and evolution. PUBLIC HEALTH RELEVANCE: Cystic fibrosis (CF) patients are highly susceptible to chronic respiratory tract infection by the common environmental microbe, Pseudomonas aeruginosa. Chronic infections greatly diminish patient quality of life, and respiratory failure, often attributable to Pseudomonas infection, accounts for >90% CF mortality. Early in life, CF patients seem to acquire the bacterial strain to which they succumb years later. Because thousands of bacterial generations elapse between initial infection and death, disease progression is an evolutionary process. We seek to better understand how these bacteria evolve in the face of constant immune system surveillance and intermittent antibiotic treatment. A characteristic feature of chronic infections is the emergence of "mutator" strains, bacteria that have high mutation rates and seemingly facilitate acquisition of multiple antibiotic resistance. We aim to investigate how "mutators" alter the pace and trajectory of evolution: we will genetically analyze strains isolated from multiple patients over time, and model conditions for mutators to arise and persist. Our goal is to help clinicians devise antibiotic therapies that minimize the likelihood that multi-drug resistance emerges during chronic infections. [unreadable] [unreadable] [unreadable] [unreadable]